The verdict: can you vibe code Timing?
Build a basic local prototype with Tauri and Swift hooks, but keep paying for Timing if you need rock-solid background tracking that survives macOS updates.
Timing's core value is not a CRUD web dashboard; it is a bulletproof native background daemon that polls macOS window states every second while keeping CPU usage under 0.5% and respecting strict OS permission sandboxes. Building a personal clone requires writing native Swift helpers for Accessibility and CGWindow APIs, piping data into local SQLite, and managing constant Apple security permission changes across macOS releases.
Estimated effort: 2-3 months of part-time native development
What you can't replicate
- Decade-long edge-case hardening against macOS system updates
- Zero-latency native memory footprint (<0.5% CPU background usage)
Founded
2011
Raised
—
Team
Boutique indie team
Cheapest paid tier
$12/mo
What Timing does
An automatic time-tracker and productivity analyzer for macOS that passively records active application windows, visited web URLs, document file paths, and calendar events with AI summaries and privacy-first local storage.
Core features
- Passive background macOS activity tracking (App windows, URLs, document paths)
- Interactive visual timeline with drag-and-drop categorization
- Rule-based auto-categorization via option-drag
- AI activity summarization and natural language insights
- Calendar and meeting detection integration
- Idle time detection and exclusion
- Local SQLite data storage with optional sync
- Exportable timesheets (PDF, CSV, XLSX)
The business
Pricing
- Professional$12/mo
- Expert$16.50/mo
- Connect$22.50/mo
Funding
Unknown / bootstrapped
Pay vs build, cumulative
Break-even at month 3 — after that, every month is money kept.
The hard parts of vibe coding Timing
- Low-level macOS Accessibility API and CGWindow API polling without draining CPU or battery
- Handling fragile macOS permissions (Screen Recording and Accessibility prompts)
- Querying exact document file paths from native browsers and office apps via AppleScript/JXA
- Maintaining second-by-second timeline state in a local SQLite database without disk bloat
How to vibecode Timing
Prerequisites
Mac computer
Required to compile and run native macOS accessibility daemons
XcodeFree
Required for Swift development and native macOS app compilation
Node.jsFree
Required for frontend web dashboard tooling if building a Tauri/web hybrid
AI coding tools
Recommended stack
| Frontend | Tailwind CSS + React (via Tauri web view) |
|---|---|
| Backend | Rust (Tauri core background daemon + macOS Accessibility hooks) |
| Database | SQLite (local application support directory) |
| Auth | None (single-user personal local app) |
| Payments | None (personal use) |
| Other | Swift / AppleScript helper scripts for window polling, Anthropic API for AI activity summaries |
Hosting & infrastructure
| Cloudflare | Hosting optional web dashboard or sync backend if needed | $0/mo |
Build guide
01Scaffold Tauri macOS Desktop Shell
Initialize a Tauri v2 project configured as a native macOS menubar and window utility, establishing the TypeScript frontend and Rust backend bridge.
Initialize a Tauri v2 project with a React and Tailwind CSS frontend template. Configure the project window to run as a macOS menubar utility app with a hidden dock icon. Set up the Rust backend entry point in `src-tauri/src/lib.rs` with basic Tauri command plumbing to communicate between the Swift/Rust layer and the React frontend. Ensure the build configuration targets macOS desktop distribution and includes necessary permissions for system tray management.02Implement Native macOS Activity Polling Daemon
Build a background Rust and Swift helper routine using the macOS Accessibility API and CGWindow API to capture active application names, window titles, and file paths every second.
Implement a background activity-polling daemon in Rust within the Tauri backend that executes every 1 second. Use macOS CoreGraphics APIs (CGWindowListCopyWindowInfo) and Accessibility APIs to query the currently active application bundle identifier, active window title, and document file path. Handle permission request flows gracefully when Accessibility access is not yet granted by the user. Ensure CPU consumption remains negligible (<0.5%) by throttling checks and caching unchanged window states.03Local SQLite Storage & Idle Detection
Configure a local SQLite database in the application support directory to persist second-by-second activity logs, alongside idle time detection based on user input inactivity.
Integrate rusqlite into the Tauri Rust backend to manage a local SQLite database stored in the macOS Application Support directory. Create tables for `activities` (id, app_name, window_title, file_path, url, start_time, end_time, duration, is_idle). Implement an idle-detection watcher using CGEventSourceSecondsSinceLastEventType to detect when the user steps away from the Mac, automatically closing active intervals and marking subsequent periods as idle time.04Interactive Timeline & Project Categorization UI
Build a React-based interactive visual timeline displaying 24-hour activity blocks, supporting drag-and-drop project assignment and option-drag rule creation.
Build a React component representing an interactive 24-hour visual timeline view. Render activity blocks grouped by application and project color codes. Implement drag-and-drop functionality to assign time blocks to custom projects. Add an option-drag modifier interaction that saves a matching rule (e.g., 'if window title contains X, assign to Project Y') into a `rules` table in SQLite so future activities auto-categorize.05AI Activity Summaries & Exporting
Connect the Anthropic API to generate natural language summaries of daily work patterns, and add report generation for CSV and JSON export.
Implement an AI summary feature in the Rust backend that aggregates the day's activity logs from SQLite, formats them into a structured text prompt, and calls the Anthropic API to generate a concise summary of what was accomplished and key productivity patterns. Build a reporting screen in React that displays total hours per project and provides export options for CSV and JSON format.
Cost vs paying for Timing
What will you build it with?
Starting total with Cursor$0 one-time
Starting costs (one-time)
- AI coding tool subscription$20.00
Total$20.00 one-time
Ongoing costs (monthly)
- Anthropic API usage for AI summaries~$2.00/mo
Total~$2.00/mo
Paying for Timing
$12.00/mo
Your time to build
40-60 hours
AI tool credits
$20.00 (one-month Cursor/Claude subscription)
Break-even
2 months
Vibe code Timing: FAQ
- Can you vibe code Timing yourself?
- Serious undertaking — 38/100 vibecodeable. Build a basic local prototype with Tauri and Swift hooks, but keep paying for Timing if you need rock-solid background tracking that survives macOS updates.
- How long does it take to vibe code Timing?
- 2-3 months of part-time native development — roughly 40-60 hours of hands-on time with an AI coding agent.
- How do you build your own Timing?
- Scoped to personal use: Tailwind CSS + React (via Tauri web view) on the front, Rust (Tauri core background daemon + macOS Accessibility hooks) behind it, SQLite (local application support directory) for data. Follow the 5-step build guide on this page — each step has a paste-ready prompt for an AI coding agent.
- How do you code your own Timing without being an expert?
- Use an AI coding tool (Cursor or Claude Code) and work in small steps: scaffold, data model, core screens, then deploy. Realistic effort: 2-3 months of part-time native development. The prompts on this page are written so the AI does the heavy lifting.
- How much does it cost to vibe code Timing instead of paying?
- About $20.00 one-time to start and ~$2.00/mo to run, versus $12.00/mo for Timing. Break-even: 2 months.
- What stack should you use to vibe code Timing?
- Tailwind CSS + React (via Tauri web view); Rust (Tauri core background daemon + macOS Accessibility hooks); SQLite (local application support directory); plus Swift / AppleScript helper scripts for window polling, Anthropic API for AI activity summaries.